Sep. 21-22, 2006 v FME Worldwide User Conference - Vancouver Working with Linear Reference Systems using FME Mark Stoakes, Safe Software.

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Sep , 2006 v FME Worldwide User Conference - Vancouver Working with Linear Reference Systems using FME Mark Stoakes, Safe Software

Linear Referencing Systems 2 National Road Network  National Research Canada Center for Topographic Information  Responsible for National Road Network  NRN model defines the road network by using an Linear Referencing System (LRS) approach  Network Linear Elements  Events along the NLE  Linear Referencing Method is the technique used to match the event to the NLE

Linear Referencing Systems 3 Linear Referencing Method

Linear Referencing Systems 4 Linear Referencing Method  Event Locations can be described by:  LRM by Percentage  from %  to %  LRM by Measure  from distance  to distance  LRM by position  from vertex #  to vertex #  Event Tables  BlockedPassage, ExitNumber, NumberOfLanes, RaodClass, RaodSurface, RouteName, RouteNumber, Structure

Linear Referencing Systems 5 Segmented Models  All attributes are on each segment  If an attribute changes along the road – between road junctions - (i.e. speed limit) then the road is segmented.

Linear Referencing Systems 6 LRS vs. Segmented RoadSurface Event NID From To PavementStatus PavementSurface

Linear Referencing Systems 7 FME Workspace  Requirement for lossless conversion between the LRS & Segmented – in both directions.  LRS  Segmented  Segmented  LRS  Support LRM %, measure & position  Preserve NLE & Segment orientation

Linear Referencing Systems 8 FME Workspaces

Linear Referencing Systems 9 Conversion Issues  LRS  Segmented  Splitting NLE into Segments based on several event tables  Coordinate projections – all data is in LL and many distance calculations  Attaching all event attributes to each segment  Segmented  LRS  Joining Segments to form NLE  Closed loops (linear rings)  New Transformers  LengthToPointCalculator & DistanceSnipper  TCL – to calculate measure attributes for %, distance, position LRM (more advanced than MeasureGenerator)